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# -*- coding: utf-8 -*-
"""Gradio_NER_App.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1jJt0EzAjNDS_YlBT_ZNjBx562ezPBpX-
"""
# !pip install -q transformers
from transformers import pipeline
ner_pipeline = pipeline("ner", model="ertyazilim/multilingual-xlm-roberta-for-ner")
text = "I am Tim and I work at Google"
ner_pipeline(text)
text_tr = "Benim adım Ali ve Trendyol'da çalışıyorum"
ner_pipeline(text_tr)
ner_pipeline(text_tr, aggregation_strategy = "simple")
def ner(text):
output = ner_pipeline(text, aggregation_strategy = "simple")
return {"text": text, "entities": output}
# !pip install -q gradio
import gradio as gr
examples = [
"My name is Tim and I live in California",
"Ich arbeite bei Google in Berlin",
"Ali, Ankaralı mı?"
]
demo = gr.Interface(
ner,
gr.Textbox(placeholder = "Enter sentence here..."),
gr.HighlightedText(),
examples = examples
)
demo.launch(share=True)
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